Real-time study on the effect of dust accumulation on performance of solar PV panels in Malaysia

Sulaiman, Shaharin Anwar; Mat, Mohamad Nur Hidayat; Guangul, Fiseha M.; Bou-Rabee, Mohammed A.

doi:10.1109/eitech.2015.7162938

Cited by 32 publications

(18 citation statements)

References 8 publications

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“…Mekhilef et al [35] interrelated amongst thickness of dust accumulated on PV module and inconsistency in proficiencies of composite climate, a significant reduction in PV module output of about 10-20 % by dust accumulation was inferred. Sulaiman et al [36] reported that external resistance could reduce PV performance by up to 85% however, concluded that water droplet from rain would not affect significantly the performance of PV modules.…”

Section: Brief Review Of Similar Research Workmentioning

confidence: 99%

Elemental composition of Dust Particles and Influence of Dust Addition on Photovoltaic Module Performance

McAsule

Gesa

Akiiga

et al. 2022

JENRR

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There is an excellence prospective for solar power practice in Nigeria by engaging solar photovoltaic (PV) units. Addition of dust on solar antennae and PV elements is a pronounced worry owing to different dust particles fouling on the module. The recitals of such devices are considerably suffering from dust addition. Dust samples involved during this study came from ash, cement, rice husk, brick dust, and sand. This paper therefore, reports the outcome of a research work on the elemental composition of dust particles and influence of dust addition on the maximum power, efficiency and performance ratio of a 3 W polycrystalline solar PV module. The electron dispersive x-ray analysis of the collected dust samples revealed silicon having the highest percentage weight composition while sulfur and nitrogen records 0 % in most of the sample apart from rice husk. The experimental measurements were conducted outdoor under 470, 715 and 756 W/m2 solar irradiation levels. Results indicated that dust addition on the solar PV module negatively affects the output power with cement dust proffering highest effect due to high percentage weight of carbon present in it. The research work revealed that solar PV modules polluted by dust particles for a period of time experienced a significant decrease in their efficiency and performance during operation. Accordingly, it is recommended that installed PV modules be cleaned routinely as dust particles hid on the solar panel naturally. Many areas have to be covered in future like construction sites, agricultural land and many more as solar power is growing exponentially in Nigeria.

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Section: Brief Review Of Similar Research Workmentioning

confidence: 99%

Elemental composition of Dust Particles and Influence of Dust Addition on Photovoltaic Module Performance

McAsule

Gesa

Akiiga

et al. 2022

JENRR

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“…Kelebaone T. et al examined the use of light sensors to operate PV cleaning units when the light passing through the PV panels was less than 20% of the atmospheric sunlight [11]. Studies in [12][13][14][15] relied on collected PV power data to estimate the impact of dust on PV panels and then model the effect of dust on PV performance. Russell K. Jones et al in [16] used a long-term observation on average soiling rates to propose an optimal schedule for PV panel cleaning in central Saudi Arabia.…”

Section: Introductionmentioning

confidence: 99%

A Sensorless Intelligent System to Detect Dust on PV Panels for Optimized Cleaning Units

Alfaris

2023

Energies

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Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high level of data prediction and processing. The AI was used in this study in order to estimate the unprovided information, emulate the provided measurements, and accommodate more input/output data. The feasibility of the proposed system is investigated using actual field data during all possible weather conditions.

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“…The losses due to soiling vary with location, human activities in the region, PV systems' design, angular position, mounting orientation, surface covering material, and climate [6,7]. The reported soiling loss rates range from as low as 0.5% reduction of PV output in a day [8], 63% in a month [9], to about 50% reduction of PV yield in 6 months [10] without cleaning. A clean low iron glass has 91% transparency [11], reducing the amount of irradiance reaching the solar cells and preventing it from generating optimum yield.…”

Section: Introductionmentioning

confidence: 99%

Soiling mapping through optical losses for Nigeria

Chanchangi

Ghosh²,

Micheli³

et al. 2022

Renewable Energy

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Real-time study on the effect of dust accumulation on performance of solar PV panels in Malaysia

Cited by 32 publications

References 8 publications

Elemental composition of Dust Particles and Influence of Dust Addition on Photovoltaic Module Performance

Elemental composition of Dust Particles and Influence of Dust Addition on Photovoltaic Module Performance

A Sensorless Intelligent System to Detect Dust on PV Panels for Optimized Cleaning Units

Soiling mapping through optical losses for Nigeria

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